Instructions to use AnanthZeke/NER-indic-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnanthZeke/NER-indic-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AnanthZeke/NER-indic-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AnanthZeke/NER-indic-bert") model = AutoModelForTokenClassification.from_pretrained("AnanthZeke/NER-indic-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.561eb42
-
Training in progress, step 1100
e0ed5a3 -
Training in progress, step 1000
9cb1cff -
Training in progress, step 900
44dd8dc -
Training in progress, step 800
1a0f2d2 -
Training in progress, step 700
1a0c7f7 -
Training in progress, step 600
e6d0f31 -
Training in progress, step 500
ce03e65 -
Training in progress, step 400
9c2a694 -
Training in progress, step 300
f1e6a6b -
Training in progress, step 200
5409ceb -
Training in progress, step 100
67cd34c -
Training in progress, step 200
6c0dc3d -
Training in progress, step 100
c46213f -
initial commit
ac1fbf4